Sarcasm is a linguistic tool that uses irony to express contempt. Its figurative nature poses a great challenge for affective systems performing sentiment analysis. Previous research in automated sarcasm detection has primarily focused on lexical, pragmatic cues found in sentences [1]}. Interjections, punctuations, sentimental shifts, etc., have been considered as major indicators of sarcasm [2]}. When such lexical cues are present in sentences, sarcasm detection can achieve high accuracy. However, sarcasm is also expressed implicitly, i.e., without the use of any explicit lexical cues. Such use of sarcasm also relies on the context which involves the presumption of commonsense and background knowledge of an event. When it comes to detecting sarcasm in a discussion forum, it may not only require understanding the context of the previous comments but also need necessary external background knowledge about the topic of discussion.
The usage of slangs and informal language also diminishes the reliance on lexical cues. This particular type of sarcasm is tough to detect [3]}.
